After the start of the Syrian Civil War in 2011-12, increasing
numbers of civilians sought refuge in neighboring countries. By May
2017, Turkey had received over 3 million refugees - the largest
refugee population in the world. Some lived in government-run camps
near the Syrian border, but many have moved to cities looking for
work and better living conditions. They faced problems of
integration, income, welfare, employment, health, education,
language, social tension, and discrimination. In order to develop
sound policies to solve these interlinked problems, a good
understanding of refugee dynamics isnecessary. This book summarizes
the most important findings of the Data for Refugees (D4R)
Challenge, which was a non-profit project initiated to improve the
conditions of the Syrian refugees in Turkey by providing a database
for the scientific community to enable research on urgent problems
concerning refugees. The database, based on anonymized mobile call
detail records (CDRs) of phone calls and SMS messages of one
million Turk Telekom customers, indicates the broad activity and
mobility patterns of refugees and citizens in Turkey for the year 1
January to 31 December 2017. Over 100 teams from around the globe
applied to take part in the challenge, and 61 teams were granted
access to the data. This book describes the challenge, and presents
selected and revised project reports on the five major themes:
unemployment, health, education, social integration, and safety,
respectively. These are complemented by additional invited chapters
describing related projects from international governmental
organizations, technological infrastructure, as well as ethical
aspects. The last chapter includes policy recommendations, based on
the lessons learned. The book will serve as a guideline for
creating innovative data-centered collaborations between industry,
academia, government, and non-profit humanitarian agencies to deal
with complex problems in refugee scenarios. It illustrates the
possibilities of big data analytics in coping with refugee crises
and humanitarian responses, by showcasing innovative approaches
drawing on multiple data sources, information visualization,
pattern analysis, and statistical analysis.It will also provide
researchers and students working with mobility data with an
excellent coverage across data science, economics, sociology, urban
computing, education, migration studies, and more.
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